Evidence map›Paper›PMID 27885709›Full record

ArticleStatistics in medicine2017

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis.

Peter C Austin, Philippe Wagner, Juan Merlo

Abstract read
In one paragraph

Article in Statistics in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  9. Factors Associated with Progression to Type 2 Diabetes among Women with Gestational Diabetes.Journal of urban health : bulletin of the New York Academy of Medicine · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Peter C AustinInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Philippe WagnerUnit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.
Juan MerloUnit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.

Funding

CIHR MOP 86508
6 · The paper itself

Abstract

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Indexed as

Proportional Hazards ModelsSurvival AnalysisCluster AnalysisHospital MortalityHumansLogistic ModelsMultilevel AnalysisMyocardial InfarctionOdds RatioOntarioclustered datafrailty modelsMedian Hazard RatioMedian Odds Ratiomultilevel analysissurvival analysis

Identifiers

PMID27885709
PMCPMC5299617

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.